Metadata-Version: 2.1
Name: torchio
Version: 0.16.3
Summary: Tools for loading, augmenting and writing 3D medical images on PyTorch.
Home-page: https://github.com/fepegar/torchio
Author: Fernando Perez-Garcia
Author-email: fernando.perezgarcia.17@ucl.ac.uk
License: MIT license
Keywords: torchio
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: Click (>=7.0)
Requires-Dist: nibabel
Requires-Dist: numpy
Requires-Dist: Python-Deprecated
Requires-Dist: scipy
Requires-Dist: SimpleITK
Requires-Dist: torch (>=1.2)
Requires-Dist: torchvision
Requires-Dist: tqdm

# [TorchIO](http://torchio.rtfd.io/)

[![PyPI downloads](https://img.shields.io/pypi/dm/torchio.svg?label=PyPI%20downloads&logo=python&logoColor=white)](https://pypi.org/project/torchio/)
[![PyPI version](https://img.shields.io/pypi/v/torchio?label=PyPI%20version&logo=python&logoColor=white)](https://pypi.org/project/torchio/)
[![Google Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/112NTL8uJXzcMw4PQbUvMQN-WHlVwQS3i)
[![Documentation status](https://img.shields.io/readthedocs/torchio?label=Docs&logo=Read%20the%20Docs)](http://torchio.rtfd.io/?badge=latest)
[![Build status](https://img.shields.io/travis/fepegar/torchio/master.svg?label=Travis%20CI%20build&logo=travis)](https://travis-ci.org/fepegar/torchio)
[![Coverage status](https://codecov.io/gh/fepegar/torchio/branch/master/graphs/badge.svg)](https://codecov.io/github/fepegar/torchio)
[![Code quality](https://img.shields.io/scrutinizer/g/fepegar/torchio.svg?label=Code%20quality&logo=scrutinizer)](https://scrutinizer-ci.com/g/fepegar/torchio/?branch=master)
[![Code maintainability](https://api.codeclimate.com/v1/badges/518673e49a472dd5714d/maintainability)](https://codeclimate.com/github/fepegar/torchio/maintainability)
[![Slack](https://img.shields.io/badge/TorchIO-Join%20on%20Slack-blueviolet?style=flat&logo=slack)](https://join.slack.com/t/torchioworkspace/shared_invite/enQtOTY1NTgwNDI4NzA1LTEzMjIwZTczMGRmM2ZlMzBkZDg3YmQwY2E4OTIyYjFhZDVkZmIwOWZkNTQzYTFmYzdiNGEwZWQ4YjgwMTczZmE)

---

### 🎉 News: the paper is out! 🎉

See the [Credits](#credits) section below for more information.

---

<table align="center">
    <tr>
        <td align="center">Original</td>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomblur">Random blur</a>
        </td>
    </tr>
    <tr>
        <td align="center"><img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/1_Lambda_mri.png" alt="Original"></td>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomblur">
                <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/2_RandomBlur_mri.gif" alt="Random blur">
            </a>
        </td>
    </tr>
    <tr>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomflip">Random flip</a>
        </td>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomnoise">Random noise</a>
        </td>
    </tr>
    <tr>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomflip">
                <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/3_RandomFlip_mri.gif" alt="Random flip">
            </a>
        </td>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomnoise">
                <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/4_Compose_mri.gif" alt="Random noise">
            </a>
        </td>
    </tr>
    <tr>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomaffine">Random affine transformation</a>
        </td>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomelasticdeformation">Random elastic transformation</a>
        </td>
    </tr>
    <tr>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomaffine">
                <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/5_RandomAffine_mri.gif" alt="Random affine transformation">
            </a>
        </td>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomelasticdeformation">
                <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/6_RandomElasticDeformation_mri.gif" alt="Random elastic transformation">
            </a>
        </td>
    </tr>
    <tr>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randombiasfield">Random bias field artifact</a>
        </td>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randommotion">Random motion artifact</a>
        </td>
    </tr>
    <tr>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randombiasfield">
                <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/7_RandomBiasField_mri.gif" alt="Random bias field artifact">
            </a>
        </td>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randommotion">
                <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/8_RandomMotion_mri.gif" alt="Random motion artifact">
            </a>
        </td>
    </tr>
    <tr>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomspike">Random spike artifact</a>
        </td>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomghosting">Random ghosting artifact</a>
        </td>
    </tr>
    <tr>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomspike">
                <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/9_RandomSpike_mri.gif" alt="Random spike artifact">
            </a>
        </td>
        <td align="center">
            <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomghosting">
                <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/10_RandomGhosting_mri.gif" alt="Random ghosting artifact">
            </a>
        </td>
    </tr>
</table>



TorchIO is a Python package containing a set of tools to efficiently
read, sample and write 3D medical images in deep learning applications
written in [PyTorch](https://pytorch.org/),
including intensity and spatial transforms
for data augmentation and preprocessing.
Transforms include typical computer vision operations
such as random affine transformations and also domain-specific ones such as
simulation of intensity artifacts due to
[MRI magnetic field inhomogeneity](http://mriquestions.com/why-homogeneity.html)
or [k-space motion artifacts](http://proceedings.mlr.press/v102/shaw19a.html).

This package has been greatly inspired by [NiftyNet](https://niftynet.io/).


## [Documentation](http://torchio.rtfd.io/)

The documentation is hosted on
[Read the Docs](http://torchio.rtfd.io/).

Please [create a new issue](https://github.com/fepegar/torchio/issues/new)
if you think something is missing.


## Credits

If you like this repository, please click on Star!

If you use this package for your research, please cite the paper:

[Pérez-García et al., 2020, *TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning*](https://arxiv.org/abs/2003.04696).


BibTeX entry:

```bibtex
@misc{fern2020torchio,
    title={TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning},
    author={Fernando Pérez-García and Rachel Sparks and Sebastien Ourselin},
    year={2020},
    eprint={2003.04696},
    archivePrefix={arXiv},
    primaryClass={eess.IV}
}
```


History
=======

0.15.0 (07-04-2020)
-------------------

* Refactor ``RandomElasticDeformation`` transform
* Make ``Subject`` inherit from ``dict``


0.14.0 (31-03-2020)
-------------------

* Add ``datasets`` module
* Add support for DICOM files
* Add documentation
* Add ``CropOrPad`` transform


0.13.0 (24-02-2020)
-------------------

* Add ``Subject`` class
* Add random blur transform
* Add lambda transform
* Add random patches swapping transform
* Add MRI k-space ghosting artefact augmentation


0.12.0 (21-01-2020)
-------------------

* Add ToCanonical transform
* Add CenterCropOrPad transform


0.11.0 (15-01-2020)
-------------------

* Add Resample transform


0.10.0 (15-01-2020)
-------------------

* Add Pad transform
* Add Crop transform


0.9.0 (14-01-2020)
------------------

* Add CLI tool to transform an image from file


0.8.0 (11-01-2020)
------------------

* Add Image class


0.7.0 (02-01-2020)
------------------

* Make transforms use PyTorch tensors consistently


0.6.0 (02-01-2020)
------------------

* Add support for NRRD


0.5.0 (01-01-2020)
------------------

* Add bias field transform


0.4.0 (29-12-2019)
------------------

* Add MRI k-space motion artefact augmentation


0.3.0 (21-12-2019)
------------------

* Add Rescale transform
* Add support for multimodal data and missing modalities


0.2.0 (2019-12-06)
------------------

* First release on PyPI.


